Triple
T2831155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiona Hill |
E62239
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Fiona Hill |
E62239
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Fiona Hill | Statement: [Fiona Hill, birthName, Fiona Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fiona Hill Context triple: [Fiona Hill, birthName, Fiona Hill]
-
A.
Fiona Hill
chosen
Fiona Hill is a British-American foreign policy expert and former U.S. National Security Council official known for her expertise on Russia and her testimony in the first Trump impeachment inquiry.
-
B.
Anne Leon
Anne Leon is known as the spouse of English character actor Michael Gough, famed for his role as Alfred in the Batman film series.
-
C.
Diana Woodward
Diana Woodward is a daughter of renowned American investigative journalist Bob Woodward.
-
D.
Verity Faulks
Verity Faulks is the wife of British novelist Sebastian Faulks, known for maintaining a private life largely out of the public eye despite her husband's literary prominence.
-
E.
Rachel Ward
Rachel Ward is a mathematician known for her influential research in applied and computational mathematics, including work in areas such as optimization and data science.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdebd5a2c81908f0e30a0ae0eb8df |
completed | March 7, 2026, 8:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8bb92b08190b1de7e6973d96301 |
completed | March 10, 2026, 9:47 a.m. |
Created at: March 6, 2026, 10:01 p.m.